线程/进程锁、池，进程的数据共享

一、线程的锁

线程与进程共有五种锁

首先说说为什么要加锁

1、LOCK与RLOCK锁

 1 import threading
 2 import time
 3 
 4 lock=threading.Lock()
 5 def func(args):
 6     time.sleep(1)
 7     lock.acquire()
 8     print(args)
 9     lock.release()
10 
11 for i in range(5):
12     t=threading.Thread()
13     t.start()
14

LOCK 与RLOCK用法相似，RLOCK可以多成加锁，然后多层解锁

2、semaphore 一次放行N个

 1 import threading
 2 import time
 3 
 4 lock=threading.BoundedSemaphore(3) #设置一次放行三个进程
 5 def func(args):
 6     lock.acquire()
 7     time.sleep(1)
 8     print(args)
 9     lock.release()
10 
11 for i in range(9):
12     t=threading.Thread(target=func,args=(i,))
13     t.start()

3、Condition 的两种方式

 1 import threading
 2 import time
 3 
 4 lock=threading.Condition()
 5 def func(args):
 6     time.sleep(1)
 7     lock.acquire()
 8     lock.wait()
 9     print(args)
10     lock.release()
11 
12 for i in range(5):
13     t=threading.Thread(target=func,args=(i,))
14     t.start()
15 
16 while True:
17     inp = int(input("请输入任意数字"))
18     lock.acquire()
19     lock.notify(inp)
20     lock.release()

方式二、

 1 import threading
 2 import time
 3 
 4 lock=threading.Condition()
 5 def task():
 6     input(">>>>")
 7     return True
 8 
 9 def func(args):
10     time.sleep(1)
11     lock.acquire()
12     lock.wait_for(task)
13     print(args)
14     lock.release()
15 
16 for i in range(5):
17     t=threading.Thread(target=func,args=(i,))
18     t.start()

4、Event锁一次放行所有线程

 1 import threading
 2 import time
 3 lock=threading.Event()
 4 def func(args):
 5     time.sleep(1)
 6     lock.wait()
 7     print(args)
 8 
 9 for i in range(5):
10     t=threading.Thread(target=func,args=(i,))
11     t.start()
12 
13 input("<<<<")
14 lock.set()

5、threading.local()原理
为每一个线程创建一个属于自己的内存来存放数据

 1 import threading
 2 import time
 3 v=threading.local()
 4 
 5 def func(args):
 6     v.phone=args  #存放数据
 7     time.sleep(1)
 8     print(v.phone,args)
 9 
10 for i in range(5):
11     t=threading.Thread(target=func,args=(i,))
12     t.start()

6、线程池设置每次可从线程池中调用的线程数

 1 from concurrent.futures import ThreadPoolExecutor
 2 import threading
 3 import time
 4 pool=ThreadPoolExecutor(2) # 线程池线程的可调用数
 5 def func(args):
 6     time.sleep(1)
 7     print(args)
 8 
 9 for i in range(5):
10     pool.submit(func,i)